Abstract
Salient object detection has many applications for computer vision field. In this paper, we have proposed a method for improving salient object detection which is a combination of global contrast and color distribution. The proposed method has three main steps: to reduce color space, to create salient map and to increase the object quality. The main problems of previous research consist of the consumption of time and the quality of salient map. The proposed method solves two above problems. We used a large dataset to test the proposed method. The proposed method’s result is better than other methods in two points: the running time and the quality of salient map.
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© 2016 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Duy Dat, N., Thanh Binh, N. (2016). Improving Salient Object via Global Contrast Combined with Color Distribution. In: Vinh, P., Barolli, L. (eds) Nature of Computation and Communication. ICTCC 2016. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 168. Springer, Cham. https://doi.org/10.1007/978-3-319-46909-6_31
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DOI: https://doi.org/10.1007/978-3-319-46909-6_31
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